how to get parse tree using python nltk?

Question

Given the following sentence:

The old oak tree from India fell down.

How can I get the following parse tree representation of the sentence usin

Answer 1

Older question, but you can use nltk together with the bllipparser. Here is a longer example from nltk. After some fiddling I myself used the following:

To install (with nltk already installed):

sudo python3 -m nltk.downloader bllip_wsj_no_aux
pip3 install bllipparser

To use:

from nltk.data import find
from bllipparser import RerankingParser

model_dir = find('models/bllip_wsj_no_aux').path
parser = RerankingParser.from_unified_model_dir(model_dir)

best = parser.parse("The old oak tree from India fell down.")

print(best.get_reranker_best())
print(best.get_parser_best())

Output:

-80.435259246021 -23.831876011253 (S1 (S (NP (NP (DT The) (JJ old) (NN oak) (NN tree)) (PP (IN from) (NP (NNP India)))) (VP (VBD fell) (PRT (RP down))) (. .)))
-79.703612178593 -24.505514522222 (S1 (S (NP (NP (DT The) (JJ old) (NN oak) (NN tree)) (PP (IN from) (NP (NNP India)))) (VP (VBD fell) (ADVP (RB down))) (. .)))

Answer 2

Here is alternative solution using StanfordCoreNLP instead of nltk. There are few library that build on top of StanfordCoreNLP, I personally use pycorenlp to parse the sentence.

First you have to download stanford-corenlp-full folder where you have *.jar file inside. And run the server inside the folder (default port is 9000).

export CLASSPATH="`find . -name '*.jar'`"
java -mx4g -cp "*" edu.stanford.nlp.pipeline.StanfordCoreNLPServer [port?] # run server

Then in Python, you can run the following in order to tag the sentence.

from pycorenlp import StanfordCoreNLP
nlp = StanfordCoreNLP('http://localhost:9000')

text = "The old oak tree from India fell down."

output = nlp.annotate(text, properties={
  'annotators': 'parse',
  'outputFormat': 'json'
})

print(output['sentences'][0]['parse']) # tagged output sentence